Improved biomarker performance for the detection of hepatocellular carcinoma by inclusion of clinical parameters

Mengjun Wang, Timothy M. Block, Jorge Marrero, Adrian M. Di Bisceglie, Karthik Devarajan, Anand Mehta

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

We have previously identified several biomarkers of hepatocellular carcinoma (HCC). The levels of three of these biomarkers were analyzed individually and in combination with the currently used marker, alpha fetoprotein (AFP), for the ability to distinguish between a diagnosis of cirrhosis (n=113) and HCC (n=164). We have utilized several novel biostatistical tools, along with the inclusion of clinical factors such as age and gender, to determine if improved algorithms could be used to increase the probability of detection of cancer. Using several of these methods, we are able to detect HCC in the background of cirrhosis with an AUC of at least 0.95. The use of clinical factors in combination with biomarker values to detect HCC is discussed.

Original languageEnglish (US)
Title of host publicationProceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2012
Pages534-538
Number of pages5
DOIs
StatePublished - 2012
Event2012 IEEE International Conference on Bioinformatics and Biomedicine, BIBM2012 - Philadelphia, PA, United States
Duration: Oct 4 2012Oct 7 2012

Publication series

NameProceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2012

Other

Other2012 IEEE International Conference on Bioinformatics and Biomedicine, BIBM2012
Country/TerritoryUnited States
CityPhiladelphia, PA
Period10/4/1210/7/12

Keywords

  • Hepatitis B virus
  • Hepatocellular Carcinoma
  • biomarkers
  • classification and regression trees
  • logistic regression
  • penalized logistic regression

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

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